ChronoGraph: A Versioned TinkerPop Graph Database

Haeusler, Martin; Trojer, Thomas; Kessler, Johannes; Farwick, Matthias; Nowakowski, Emmanuel; Breu, Ruth

doi:10.1007/978-3-319-94809-6_12

Cited by 6 publications

(6 citation statements)

References 22 publications

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“…Since temporal graphs can grow very large in size, the questions of secondary storage are crucial. In this context, one can develop a temporal graph management system by designing a dedicated storage engine such as a file system layout [17] or a temporal key/value store [18]. However, regarding the fact that most real-world temporal graphs are more likely to exponentially grow in size, the backend storage engine should offer scalability.…”

Section: Related Workmentioning

confidence: 99%

“…These methods are mainly motivated by concepts of logging and checkpointing which reflects on lessons learned from classical techniques of database state recovery [23], [24]. The Log approach followed by Raphtory [25], ChronoGraph [26] and TAG [5], [6] consists of storing graph updates as a series of timestamped logs such that any graph state can be recovered by reloading all logs with a relative timestamp lower than or equal to the requested one. Whereas the Copy approach consists of materializing and persisting graph snapshots.…”

Section: Related Workmentioning

confidence: 99%

“…Next, for every retrieved edge operation , the algorithm gets the event and the id of the target vertex (lines [18][19][20]. Note that functions f E , f G and α are defined in section III and T arget(x) returns the id of the target vertex of an edge x.…”

Section: B Queryingmentioning

confidence: 99%

See 2 more Smart Citations

Clock-G: A temporal graph management system with space-efficient storage technique

Massri

Miklós

Raipin

et al. 2022

2022 IEEE 38th International Conference on Data Engineering (ICDE)

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Clock-G: A temporal graph management system with space-efficient storage technique

Massri

Miklós

Raipin

et al. 2022

2022 IEEE 38th International Conference on Data Engineering (ICDE)

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“…Tracking this history requires a fitting data structure: thankfully, there has been a recent push towards adding temporal capabilities to graph databases, with the ability to efficiently store and navigate the history of an entire labelled attributed graph. Two examples include Greycat [18] and ChronoGraph [17].…”

Section: Storage and Retrieval Of Historic Datamentioning

confidence: 99%

Temporal Models for History-Aware Explainability

Parra-Ullauri

García-Domínguez

Garcia-Paucar

et al. 2020

Proceedings of the 12th System Analysis and Modelling Conference

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On one hand, there has been a growing interest towards the application of AI-based learning and evolutionary programming for selfadaptation under uncertainty. On the other hand, self-explanation is one of the self-* properties that has been neglected. This is paradoxical as self-explanation is inevitably needed when using such techniques. In this paper, we argue that a self-adaptive autonomous system (SAS) needs an infrastructure and capabilities to be able to look at its own history to explain and reason why the system has reached its current state. The infrastructure and capabilities need to be built based on the right conceptual models in such a way that the system's history can be stored, queried to be used in the context of the decision-making algorithms.The explanation capabilities are framed in four incremental levels, from forensic self-explanation to automated history-aware (HA) systems. Incremental capabilities imply that capabilities at Level should be available for capabilities at Level + 1. We demonstrate our current reassuring results related to Level 1 and Level 2, using temporal graph-based models. Specifically, we explain how Level 1 supports forensic accounting after the system's execution. We also present how to enable on-line historical analyses while the self-adaptive system is running, underpinned by the capabilities provided by Level 2. An architecture which allows recording of temporal data that can be queried to explain behaviour has been presented, and the overheads that would be imposed by live analysis are discussed. Future research opportunities are envisioned. CCS CONCEPTS• Software and its engineering → System modeling languages; Integration frameworks; Model-driven software engineering.

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“…Real graphs, however, are dynamic [12] such that their topology is subject to continuous changes. In this context, a new emphasis is being placed to support time as a first class citizen in graph management systems [13,14,15,16]. Most of these systems rely on real-world temporal graphs to evaluate their proposed methods.…”

Section: Introductionmentioning

confidence: 99%